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Noise removal methods on ambulatory EEG: A Survey
[article]
2023
arXiv
pre-print
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Further, the literature survey shows that the pattern recognition required to detect ambulatory method, eye open and close, varies with different conditions of EEG datasets. ...
This is, in turn, necessitates the identification of pattern recognition technique to effectively distinguish EEG noise data from a various condition of EEG data. ...
In our research, we focus on the GRU algorithm as a variant of RNNs for emotion recognition using EEG data. ...
arXiv:2308.02437v1
fatcat:aurut63vjngmdc555z3ppshjoe
A Survey on Emotion Recognition from EEG Signals for Autism Spectrum Disorder
2018
International Journal of Computer Applications
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Here the deep learning algorithm gives better results for autism recognition with the emotions such as happy, calm, anger and scared. ...
This paper analysis the existing works on detection of autism spectrum disorder from EEG signal. Various filtering technique and classification are presented. ...
Emotion Recognition" EEG-based emotion research is in a preliminary stage. ...
doi:10.5120/ijca2018916474
fatcat:mnnktzfeefad7amcv677742wve
Graph Neural Networks in EEG-based Emotion Recognition: A Survey
[article]
2024
arXiv
pre-print
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Besides, there is neither a comprehensive review nor guidance for constructing GNNs in EEG-based emotion recognition. ...
Since dependencies within brain regions are closely related to emotion, a significant trend is to develop Graph Neural Networks (GNNs) for EEG-based emotion recognition. ...
We hope that this survey will provide clear guidance for building GNNs in the field of EEG-based emotion recognition. ...
arXiv:2402.01138v1
fatcat:yli74hcj4vgehiw6lt5nkaxrau
Guest Editorial: Advanced Machine-Learning Methods for Brain-Machine Interfacing or Brain-Computer Interfacing
2021
IEEE/ACM Transactions on Computational Biology & Bioinformatics
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They construct 6 transfer scenarios based on the original EEG signals provided by the Bonn University to verify the performance of the proposed O-T-TSK-FC and introduce some baselines for a benchmarking ...
Ç T HIS special section of the IEEE/ACM Transactions on Computational Biology and Bioinformatics is a selection of 7 papers presented as a special section on Advanced Machine-Learning Methods for Brain-Machine ...
What's more, they studied the key electrodes for EEG emotion recognition, which is of guiding significance for the development of wearable EEG devices. ...
doi:10.1109/tcbb.2021.3078145
fatcat:hojaokclpjhgpcqob5jbwrlktm
Analysis of Emotion Recognition Model Using Electroencephalogram (EEG) Signals Based on Stimuli Text
2021
Turkish Journal of Computer and Mathematics Education
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For this reason, this study aims to test the emotion recognition experiment by stimulating sentiment-tones using EEG. ...
The dataset of emotional annotation was carried out manually based on four classifications, specifically: happiness, sadness, fear, and anger. ...
: An Interdisciplinary Review of
Models, Methods, and Their Applications [26]
Brain Wave usage
Emotion classification based on brain wave: a survey
[27], Emotion Analysis using Different Stimuli with ...
doi:10.17762/turcomat.v12i3.910
fatcat:rrhljfw56fbaxl4bxi3pcjjp5a
Representation Learning and Pattern Recognition in Cognitive Biometrics: A Survey
2022
Sensors
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There is a major need to summarize the latest developments in this field. Existing surveys have mainly focused on a small subset of cognitive biometric modalities, such as EEG and ECG. ...
Recent research has demonstrated great potential for using cognitive biometrics in versatile applications, including biometric recognition and cognitive and emotional state recognition. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s22145111
pmid:35890799
pmcid:PMC9320620
fatcat:7cniceltrbfkjk6hxfqij5yegm
Machine Learning Strategies to Improve Generalization in EEG-based Emotion Assessment: a Systematic Review
[article]
2024
arXiv
pre-print
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2022 pre-print arXiv:2212.08744v1 fatcat:qoy5gjyicvbohbswix76uad3k4
a search query focusing on modern machine learning techniques for generalization in EEG-based emotion assessment. ...
A systematic review on machine-learning strategies for improving generalizability (cross-subjects and cross-sessions) electroencephalography (EEG) based in emotion classification was realized. ...
In Chai et al. (2017) ASFM is adopted for EEG-based Emotion Recognition. ...
arXiv:2212.08744v2
fatcat:5mgpbkp2xnanpeurmlevmpl3aq
EEG based Emotion Recognition and Classification: a Review
2021
International Research Journal on Advanced Science Hub
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Our analysis is based on extracted features and classification methods of emotion recognition. ...
This paper provides an overview of comparative study of various techniques of emotion recognition from EEG signals. ...
In this study we have surveyed the various methods of emotion recognition from EEG signals. ...
doi:10.47392/irjash.2021.131
fatcat:gzujf5t33ndadj6qkgzraqeb74
Identification of Emotion Using Electroencephalogram by Tunable Q-Factor Wavelet Transform and Binary Gray Wolf Optimization
2021
Frontiers in Computational Neuroscience
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The results show that the proposed method has good performance indicators in the recognition of multiple types of EEG emotion signals, and has a better performance improvement compared with the traditional ...
Emotional brain-computer interface based on electroencephalogram (EEG) is a hot issue in the field of human-computer interaction, and is also an important part of the field of emotional computing. ...
., and Yu, C. (2016). ReliefF-Based EEG sensor selection methods for emotion recognition. ...
doi:10.3389/fncom.2021.732763
pmid:34566614
pmcid:PMC8455931
fatcat:hybc7qrtorasdn453s57kblysy
Technology Development for Unblessed People using BCI: A Survey
2012
International Journal of Computer Applications
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So in this paper, we present a review on the progress of research efforts and then we analyze the challenges in BCI research and development for unblessed people. ...
Here, a general Electro-Encephalogram (EEG) based BCI system is discussed which can assist the paralyzed or physically or mentally challenged people in performing their various routine tasks or applications ...
An EEG and EMG signal based system for classifying multiple facial expressions. 12 Emotion Classification Based on Gamma-band EEG [16] . ...
doi:10.5120/4920-7142
fatcat:tp5ymaxvcjaubeg7cvuu2mmfmm
Detection of stress and emotion recognition using EEG signal
2022
AIP Conference Proceedings
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Brain signal-based emotion detection is one of the best methods for detecting human emotion and stress, which leads to an accurate result. ...
It can help to detect human mental stress & emotion with sentiment analysis. Hence, there is a need for a system that is accurate, precise, and reliable. ...
Due to those issues, there is a need for human emotion-based stress recognition through the EEG signal & sentiment analysis, feature extraction, and Classification is a popular process these days. ...
doi:10.1063/5.0109242
fatcat:ralwz5ce3zafjme2lbjnnhmcna
EEG-Based Estimation on the Reduction of Negative Emotions for Illustrated Surgical Images
2020
Sensors
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The recent progress of deep learning-based classification models has improved the accuracy of emotion recognition in EEG signals. ...
We further execute a self-assessed user survey to prove that the emotions recognized from EEG signals effectively represent user-annotated emotions. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s20247103
pmid:33322359
fatcat:q77sqmzuinezlc5hmqb62n6peu
A Pragmatic Approach for EEG-based Affect Classification
2021
International Journal of Intelligent Systems and Applications in Engineering
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EEG Dataset (SEED) and performance of popular classifiers are assessed. ...
To overcome this, proposed work presents a novel general framework for affect-based cognitive analysis. ...
In [3] , a thorough survey of existing research for emotion recognition using EEG signals have been presented. ...
doi:10.18201/ijisae.2021473635
fatcat:7k56ulour5ccraduselnzvt4pu
EEG-Based BCI Emotion Recognition: A Survey
2020
Sensors
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Our survey gives an overview of datasets, emotion elicitation methods, feature extraction and selection, classification algorithms, and performance evaluation. ...
This article performs a survey of the pertinent scientific literature from 2015 to 2020. ...
EEG-Based BCI Systems for Emotion Recognition Figure 3 presents the structure of an EEG-based BCI system for emotion recognition. ...
doi:10.3390/s20185083
pmid:32906731
pmcid:PMC7570756
fatcat:jjv5avqr3bbypp7cwgpbhmu5ly
A Survey on Physiological Signal-Based Emotion Recognition
2022
Bioengineering
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Emotion recognition poses its own set of challenges that are very important to address for a robust system. ...
Existing review papers on emotion recognition based on physiological signals surveyed only the regular steps involved in the workflow of emotion recognition such as pre-processing, feature extraction, ...
EEG data pre-processing, feature engineering, selection of classical and deep learning models for EEG-based emotion recognition are discussed. ...
doi:10.3390/bioengineering9110688
pmid:36421089
pmcid:PMC9687364
fatcat:pl7axqqgmfdf7nhj525zaue7t4
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